AIMC Topic: Myocardial Ischemia

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Prognostic Value of a Coronary Computed Tomography Angiography-Derived Ischemia Algorithm: Comparison Against Hybrid Coronary Computed Tomography Angiography/Positron Emission Tomography Imaging.

Journal of the American Heart Association
BACKGROUND: Artificial intelligence-guided quantitative computed tomography ischemia (AI-QCT) is a novel machine-learning method for predicting myocardial ischemia from coronary computed tomography angiography (CCTA). This observational cohort study ...

Etiology-Agnostic Diagnosis of Early Myocardial Ischemia via AI-Driven Label-Free Spectral Histopathology.

Analytical chemistry
Myocardial ischemia is a core pathological mechanism in diverse fatal diseases and can be triggered by multiple factors. Diagnosing early myocardial ischemia (EMI) caused by nontraditional factors (e.g., drugs or stress) remains challenging due to su...

Ischemic heart disease mortality due to fine particulate matter in Seoul between 2016 and 2020.

BMC public health
BACKGROUND: Ischemic heart disease (IHD) continues to rank among the leading global causes of mortality, consistently linked to long-term exposure to fine particulate matter (PM). Despite a declining trend in the annual average PM concentration in Se...

A practical review of stress perfusion cardiac magnetic resonance imaging for the management of coronary artery disease.

Current opinion in cardiology
PURPOSE OF REVIEW: Stress perfusion cardiac magnetic resonance imaging (CMR) has gained increasing adoption across North America and Europe for the evaluation of symptomatic suspected or established ischemic heart disease (IHD).

A preliminary study on cause‑of‑death discrimination and the pathological stage identification in acute ischemia heart disease (AIHD) based on plasma lipidomic technique and machine learning algorithms.

International journal of legal medicine
The sudden death discrimination of acute ischemia heart disease (AIHD) and the determination of the AIHD pathological stage are the difficulties in forensic medicine. More potential biomarkers with high sensitivity and specificity still need to be id...

Developing cardiac digital twin populations powered by machine learning provides electrophysiological insights in conduction and repolarization.

Nature cardiovascular research
Large-cohort imaging and diagnostic studies often assess cardiac function but overlook underlying biological mechanisms. Cardiac digital twins (CDTs) are personalized physics-constrained and physiology-constrained in silico representations, uncoverin...

Feasibility exploration of myocardial blood flow synthesis from a simulated static myocardial computed tomography perfusion via a deep neural network.

Journal of X-ray science and technology
BACKGROUND:  Myocardial blood flow (MBF) provides important diagnostic information for myocardial ischemia. However, dynamic computed tomography perfusion (CTP) needed for MBF involves multiple exposures, leading to high radiation doses.

Artificial Intelligence in Ischemic Heart Disease Prevention.

Current cardiology reports
PURPOSE OF REVIEW: This review discusses the transformative potential of artificial intelligence (AI) in ischemic heart disease (IHD) prevention. It explores advancements of AI in predictive modeling, biomarker discovery, and cardiovascular imaging. ...

Noninvasive machine-learning models for the detection of lesion-specific ischemia in patients with stable angina with intermediate stenosis severity on coronary CT angiography.

Physical and engineering sciences in medicine
This study proposed noninvasive machine-learning models for the detection of lesion-specific ischemia (LSI) in patients with stable angina with intermediate stenosis severity based on coronary computed tomography (CT) angiography. This single-center ...